An efficient quantization technique for wavelet coefficients of fingerprint images

In this paper, a novel quantization scheme for the wavelet coefficients is introduced. Using the wavelet packet transform (WPT) and lattice vector quantization (LVQ), we present here a new lattice optimization scheme based on an accurate model for the distribution of the wavelet coefficients. The model is based on the generalized gaussian distribution (GGD). A least squares algorithm on a non-linear function of the shape parameter is formulated to estimate the model parameters. The proposed algorithm adapts to non-stationarity in input images and to given bit rates. Compared to other wavelet-based algorithms, the technique proposed here results in higher reconstructed image qualities for identical bit rates.